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  1. Life, Local Constraints and Meaning Generation. An Evolutionary Approach to Cognition (2015).Christophe Menant - manuscript
    The relations between life and cogntion have been addressed through different perspectives [Stewart 1996, Boden 2001, Bourgine and Stewart 2004, van Duijn & all 2006, Di Paolo 2009]. We would like here to address that subject by relating life to cognition through a process of meaning generation. Life emerged on earth as a far from thermodynamic equilibrium performance that had to maintain herself. Life is charactertized by a ‘stay alive’ constraint that has to be satisfied (such constraint can be included (...)
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  2. “Even an AI Could Do That”.Emanuele Arielli - forthcoming - Http://Manovich.Net/Index.Php/Projects/Artificial-Aesthetics.
    Chapter 1 of the ongoing online publication "Artificial Aesthetics: A Critical Guide to AI, Media and Design", Lev Manovich and Emanuele Arielli -/- Book information: Assume you're a designer, an architect, a photographer, a videographer, a curator, an art historian, a musician, a writer, an artist, or any other creative professional or student. Perhaps you're a digital content creator who works across multiple platforms. Alternatively, you could be an art historian, curator, or museum professional. -/- You may be wondering how (...)
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  3. Computing Machinery and Sexual Difference: The Sexed Presuppositions Underlying the Turing Test.Amy Kind - forthcoming - In Jennifer McWeeny & Keya Maitra (eds.), Feminist Philosophy of Mind.
    In his 1950 paper “Computing Machinery and Intelligence,” Alan Turing proposed that we can determine whether a machine thinks by considering whether it can win at a simple imitation game. A neutral questioner communicates with two different systems – one a machine and a human being – without knowing which is which. If after some reasonable amount of time the machine is able to fool the questioner into identifying it as the human, the machine wins the game, and we should (...)
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  4. Egocentric Bias and Doubt in Cognitive Agents.Nanda Kishore Sreenivas & Shrisha Rao - forthcoming - 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, May 2019.
    Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out on capturing the effects of biases humans are susceptible to. This work presents a method to model egocentric bias, the real-life tendency to emphasize one's own opinion heavily when presented with multiple opinions. We use a symmetric distribution, centered at an agent's own opinion, as opposed to the Bounded Confidence (BC) model used in (...)
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  5. AI-Aesthetics and the Anthropocentric Myth of Creativity.Emanuele Arielli & Lev Manovich - 2022 - NODES 1 (19-20).
    Since the beginning of the 21st century, technologies like neural networks, deep learning and “artificial intelligence” (AI) have gradually entered the artistic realm. We witness the development of systems that aim to assess, evaluate and appreciate artifacts according to artistic and aesthetic criteria or by observing people’s preferences. In addition to that, AI is now used to generate new synthetic artifacts. When a machine paints a Rembrandt, composes a Bach sonata, or completes a Beethoven symphony, we say that this is (...)
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  6. AI’s Role in Creative Processes: A Functionalist Approach.Leonardo Arriagada & Gabriela Arriagada-Bruneau - 2022 - Odradek. Studies in Philosophy of Literature, Aesthetics, and New Media Theories 8 (1):77-110.
    From 1950 onwards, the study of creativity has not stopped. Today, AI has revitalised debates on the subject. That is especially controversial in the artworld, as the 21st century already features AI-generated artworks. Without discussing issues about AI agency, this article argues for AI’s creativity. For this, we first present a new functionalist understanding of Margaret Boden’s definition of creativity. This is followed by an analysis of empirical evidence on anthropocentric barriers in the perception of AI’s creative capabilities, which is (...)
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  7. ANNs and Unifying Explanations: Reply to Erasmus, Brunet, and Fisher.Yunus Prasetya - 2022 - Philosophy and Technology 35 (2):1-9.
    In a recent article, Erasmus, Brunet, and Fisher (2021) argue that Artificial Neural Networks (ANNs) are explainable. They survey four influential accounts of explanation: the Deductive-Nomological model, the Inductive-Statistical model, the Causal-Mechanical model, and the New-Mechanist model. They argue that, on each of these accounts, the features that make something an explanation is invariant with regard to the complexity of the explanans and the explanandum. Therefore, they conclude, the complexity of ANNs (and other Machine Learning models) does not make them (...)
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  8. Measuring Intelligence and Growth Rate: Variations on Hibbard's Intelligence Measure.Samuel Alexander & Bill Hibbard - 2021 - Journal of Artificial General Intelligence 12 (1):1-25.
    In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard’s idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competitors that they defeat; and second, one specific (somewhat arbitrary) method for measuring said growth rates. Whereas Hibbard’s intelligence measure is based on the latter growth-rate-measuring method, we survey other methods (...)
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  9. Making AI Intelligible: Philosophical Foundations.Herman Cappelen & Josh Dever - 2021 - New York, USA: Oxford University Press.
    Can humans and artificial intelligences share concepts and communicate? Making AI Intelligible shows that philosophical work on the metaphysics of meaning can help answer these questions. Herman Cappelen and Josh Dever use the externalist tradition in philosophy to create models of how AIs and humans can understand each other. In doing so, they illustrate ways in which that philosophical tradition can be improved. The questions addressed in the book are not only theoretically interesting, but the answers have pressing practical implications. (...)
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  10. Towards Knowledge-Driven Distillation and Explanation of Black-Box Models.Roberto Confalonieri, Guendalina Righetti, Pietro Galliani, Nicolas Toquard, Oliver Kutz & Daniele Porello - 2021 - In Proceedings of the Workshop on Data meets Applied Ontologies in Explainable {AI} {(DAO-XAI} 2021) part of Bratislava Knowledge September {(BAKS} 2021), Bratislava, Slovakia, September 18th to 19th, 2021. CEUR 2998.
    We introduce and discuss a knowledge-driven distillation approach to explaining black-box models by means of two kinds of interpretable models. The first is perceptron (or threshold) connectives, which enrich knowledge representation languages such as Description Logics with linear operators that serve as a bridge between statistical learning and logical reasoning. The second is Trepan Reloaded, an ap- proach that builds post-hoc explanations of black-box classifiers in the form of decision trees enhanced by domain knowledge. Our aim is, firstly, to target (...)
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  11. Why Friendly AIs Won’T Be That Friendly: A Friendly Reply to Muehlhauser and Bostrom.Robert James M. Boyles & Jeremiah Joven Joaquin - 2020 - AI and Society 35 (2):505–507.
    In “Why We Need Friendly AI”, Luke Muehlhauser and Nick Bostrom propose that for our species to survive the impending rise of superintelligent AIs, we need to ensure that they would be human-friendly. This discussion note offers a more natural but bleaker outlook: that in the end, if these AIs do arise, they won’t be that friendly.
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  12. A Tale of Two Deficits: Causality and Care in Medical AI.Melvin Chen - 2020 - Philosophy and Technology 33 (2):245-267.
    In this paper, two central questions will be addressed: ought we to implement medical AI technology in the medical domain? If yes, how ought we to implement this technology? I will critically engage with three options that exist with respect to these central questions: the Neo-Luddite option, the Assistive option, and the Substitutive option. I will first address key objections on behalf of the Neo-Luddite option: the Objection from Bias, the Objection from Artificial Autonomy, the Objection from Status Quo, and (...)
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  13. DNAOS for KREMMS: A Distributed Platform for Knowledge Resource Entitlement, Modeling, Management, and Sharing.Andre Cusson - 2020 - Journal of Knowledge Structures and Systems 1 (1):117-133.
    This article is a knowledge technology case study of DNAOS, a distributed platform for Knowledge Resource Entitlement, Modeling, Management, and Sharing (KREMMS). Some historical aspects of its design, development, and release are briefly discussed, after which the DNAOS technology is commented upon from the specific viewpoint of KREMMS. At the core of this platform is the conception of knowledge as a natural phenomenon, which conception is reflected in the ontology of this technology: Fundamental knowledge structures and structuring principles, believed to (...)
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  14. Acquisition of Autonomy in Biotechnology and Artificial Intelligence.Philippe Gagnon, Mathieu Guillermin, Olivier Georgeon, Juan R. Vidal & Béatrice de Montera - 2020 - In S. Hashimoto N. Callaos (ed.), Proceedings of the 11th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC 2020, Volume II. Winter Garden: International Institute for Informatics and Systemics. pp. 168-172.
    This presentation discusses a notion encountered across disciplines, and in different facets of human activity: autonomous activity. We engage it in an interdisciplinary way. We start by considering the reactions and behaviors of biological entities to biotechnological intervention. An attempt is made to characterize the degree of freedom of embryos & clones, which show openness to different outcomes when the epigenetic developmental landscape is factored in. We then consider the claim made in programming and artificial intelligence that automata could show (...)
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  15. Ethics, Prosperity, and Society: Moral Evaluation Using Virtue Ethics and Utilitarianism.Aditya Hegde, Vibhav Agarwal & Shrisha Rao - 2020 - 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020).
    Modelling ethics is critical to understanding and analysing social phenomena. However, prior literature either incorporates ethics into agent strategies or uses it for evaluation of agent behaviour. This work proposes a framework that models both, ethical decision making as well as evaluation using virtue ethics and utilitarianism. In an iteration, agents can use either the classical Continuous Prisoner's Dilemma or a new type of interaction called moral interaction, where agents donate or steal from other agents. We introduce moral interactions to (...)
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  16. Intelligence Via Ultrafilters: Structural Properties of Some Intelligence Comparators of Deterministic Legg-Hutter Agents.Samuel Alexander - 2019 - Journal of Artificial General Intelligence 10 (1):24-45.
    Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg- Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose an elegant answer (...)
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  17. Legg-Hutter Universal Intelligence Implies Classical Music is Better Than Pop Music for Intellectual Training.Samuel Alexander - 2019 - The Reasoner 13 (11):71-72.
    In their thought-provoking paper, Legg and Hutter consider a certain abstrac- tion of an intelligent agent, and define a universal intelligence measure, which assigns every such agent a numerical intelligence rating. We will briefly summarize Legg and Hutter’s paper, and then give a tongue-in-cheek argument that if one’s goal is to become more intelligent by cultivating music appreciation, then it is bet- ter to use classical music (such as Bach, Mozart, and Beethoven) than to use more recent pop music. The (...)
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  18. On the Possibility of Emotional Robots.Godwin Darmanin - 2019 - Revista de Filosofia Aurora 31 (54).
    In this article, I examine whether the possibility exists that in the foreseeable future, robot technology will permit the development of emotional robots. As the title suggests, the content is of a technological as well as of a philosophical nature. As a matter of fact, my aim in writing this paper was that of bridging two distinctive fields in a world where humanity has become accustomed to technological innovations while overlooking any consequential complications arising from such inventions. To this end, (...)
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  19. Robotic Nudges for Moral Improvement Through Stoic Practice.Michał Klincewicz - 2019 - Techné: Research in Philosophy and Technology 23 (3):425-455.
    This paper offers a theoretical framework that can be used to derive viable engineering strategies for the design and development of robots that can nudge people towards moral improvement. The framework relies on research in developmental psychology and insights from Stoic ethics. Stoicism recommends contemplative practices that over time help one develop dispositions to behave in ways that improve the functioning of mechanisms that are constitutive of moral cognition. Robots can nudge individuals towards these practices and can therefore help develop (...)
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  20. A Non Monotonic Reasoning Framework for Goal-Oriented Knowledge Adaptation.Antonio Lieto, Federico Perrone, Gian Luca Pozzato & Eleonora Chiodino - 2019 - In Paglieri (ed.), Proceedings of AISC 2019. Rome: Università degli Studi di Roma Tre. pp. 12-14.
    In this paper we present a framework for the dynamic and automatic generation of novel knowledge obtained through a process of commonsense reasoning based on typicality-based concept combination. We exploit a recently introduced extension of a Description Logic of typicality able to combine prototypical descriptions of concepts in order to generate new prototypical concepts and deal with problem like the PET FISH (Osherson and Smith, 1981; Lieto & Pozzato, 2019). Intuitively, in the context of our application of this logic, the (...)
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  21. A Description Logic Framework for Commonsense Conceptual Combination Integrating Typicality, Probabilities and Cognitive Heuristics.Antonio Lieto & Gian Luca Pozzato - 2019 - Journal of Experimental and Theoretical Artificial Intelligence:1-39.
    We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of the combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC + TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition. We first extend the logic of typicality ALC + TR by typicality inclusions of the (...)
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  22. Predicting Whether a Couple is Going to Get Divorced or Not Using Artificial Neural Networks.Ibrahim M. Nasser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (10):49-55.
    In this paper, an artificial neural network (ANN) model was developed and validated to predict whether a couple is going to get divorced or not. Prediction is done based on some questions that the couple answered, answers of those questions were used as the input to the ANN. The model went through multiple learning-validation cycles until it got 100% accuracy.
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  23. CesimaDigital: A Tool for the History of Science.Odécio Souza - 2019 - Circumscribere: International Journal for the History of Science 24.
    This text is about the use of an Artificial Intelligence tool within the CESIMA's Digital Library.
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  24. Will Hominoids or Androids Destroy the Earth? —A Review of How to Create a Mind by Ray Kurzweil (2012) (Review Revised 2019).Michael Starks - 2019 - In Suicidal Utopian Delusions in the 21st Century -- Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2019 4th Edition Michael Starks. Las Vegas, NV USA: Reality Press. pp. 265-277.
    Some years ago, I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...)
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  25. Dreyfus on the “Fringe”: Information Processing, Intelligent Activity, and the Future of Thinking Machines.Jeffrey White - 2019 - AI and Society 34 (2):301-312.
    From his preliminary analysis in 1965, Hubert Dreyfus projected a future much different than those with which his contemporaries were practically concerned, tempering their optimism in realizing something like human intelligence through conventional methods. At that time, he advised that there was nothing “directly” to be done toward machines with human-like intelligence, and that practical research should aim at a symbiosis between human beings and computers with computers doing what they do best, processing discrete symbols in formally structured problem domains. (...)
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  26. Epiphany Philosophers: Afterword.Rowan Williams - 2019 - Zygon 54 (4):1036-1044.
    Being a theist makes a difference, but not so much to what propositions we assent to, nor to an expanded ontology of spiritual entities. Rather, it is concerned with what commitments we enter into, and involves a participatory engagement with a broader reality then we might have supposed was possible. Embodied practices are a crucial part of the contemplative path, which draws on the wisdom of the body. This leads on to a “labor of culture.” Our present culture is not (...)
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  27. Study on Effect of Shared Investing Strategy on Trust in AI.N. YokoiRyosuke & N. Kazuya - 2019 - Japanese Journal of Experimental 59 (1):46-50.
    This study examined the determinants of trust in artificial intelligence (AI) in the area of asset management. Many studies of risk perception have found that value similarity determines trust in risk managers. Some studies have demonstrated that value similarity also influences trust in AI. AI is currently employed in a diverse range of domains, including asset management. However, little is known about the factors that influence trust in asset management-related AI. We developed an investment game and examined whether shared investing (...)
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  28. Smart Walking System Based on Artificial Intelligence.Vanita Babanne, Simranjeet Kaur, Tejal Mehta, Divya Mulay & Rachana Nagarkar - 2018 - International Journal of Research in Engineering, Science and Management 1 (12).
    This paper shows the smart walking stick based on ultrasonic sensors and Arduino for outwardly debilitated individuals. There are roughly 37 million individuals over the globe who are visually impaired as indicated by the World Health Organization. Individuals with visual inabilities are regularly subjected to outer help which can be given by people, trained dogs, or electronic gadgets as supportive networks for basic assistance. Thus, this played as the motivation to develop a smart cane white stick to survive these restrictions (...)
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  29. AISC 17 Talk: The Explanatory Problems of Deep Learning in Artificial Intelligence and Computational Cognitive Science: Two Possible Research Agendas.Antonio Lieto - 2018 - In Proceedings of AISC 2017.
    Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical problem (...)
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  30. Heterogeneous Proxytypes Extended: Integrating Theory-Like Representations and Mechanisms with Prototypes and Exemplars.Antonio Lieto - 2018 - In Advances in Intelligent Systems and Computing: Proceedings of BICA. Springer.
    The paper introduces an extension of the proposal according to which conceptual representations in cognitive agents should be intended as heterogeneous proxytypes. The main contribution of this paper is in that it details how to reconcile, under a heterogeneous representational perspective, different theories of typicality about conceptual representation and reasoning. In particular, it provides a novel theoretical hypothesis - as well as a novel categorization algorithm called DELTA - showing how to integrate the representational and reasoning assumptions of the theory-theory (...)
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  31. Artificial Intelligence in Health Care: Enabling Informed Care.Tarassenko Lionel & Watkinson Peter - 2018 - The Lancet 1 (1):21-24.
    We read with interest the Lancet Editorial on artificial intelligence (AI) in health care (Dec 23, 2017, p 2739).1 Deep learning as a form of AI risks being overhyped. Deep neural networks contain multiple layers of nodes connected by adjustable weights. Learning occurs by adjusting these weights until the desired input-to-output function is achieved.2 With many millions of weights, huge amounts of data are required for learning, a process facilitated by recent increases in computational power. However, the learning algorithm, known (...)
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  32. The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI.Fernando Martínez-Plumed, Bao Sheng Loe, Peter Flach, Sean O. O. HEigeartaigh, Karina Vold & José Hernández-Orallo - 2018 - In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence Evolution of the contours of AI. pp. 5180-5187.
    We present nine facets for the analysis of the past and future evolution of AI. Each facet has also a set of edges that can summarise different trends and contours in AI. With them, we first conduct a quantitative analysis using the information from two decades of AAAI/IJCAI conferences and around 50 years of documents from AI topics, an official database from the AAAI, illustrated by several plots. We then perform a qualitative analysis using the facets and edges, locating AI (...)
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  33. The Principle of Self-Embodiment Architectonic Philosophy of Technique.Bernhard J. Mitterauer - 2018 - Journal of Global Issues and Solutions 18 (3).
    The essence of the Architectonic Philosophy of Technique is the human self-embodiment in ontogenetic, evolutionary and permanent times (Mitterauer, 1989; 2009). These time conceptions may allow the interpretation of technical processes of self-embodiment and challenge the concept of the soul. The existence of the soul in timeless permanence is my fundamental argument that technical embodiments in robots can only be generated in ontogenetic and evolutionary time periods, but not in permanence. Admittedly, the concept of the soul does not play a (...)
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  34. Astrocyte-Synapse Receptor Coupling in Tripartite Synapses: A Mechanism for Self-Observing Robots.Bernhard J. Mitterauer - 2018 - Advances in Bioscience and Biotechnology 9 (2):63-82.
    A model of an intentional self-observing system is proposed based on the structure and functions of astrocyte-synapse interactions in tripartite synapses. Astrocyte-synapse interactions are cyclically organized and operate via feedforward and feedback mechanisms, formally described by proemial counting. Synaptic, extrasynaptic and astrocyte receptors are interpreted as places with the same or different quality of information processing described by the combinatorics of tritograms. It is hypothesized that receptors on the astrocytic membrane may embody intentional programs that select corresponding synaptic and extrasynaptic (...)
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  35. Experiences in Mining Educational Data to Analyze Teacher's Performance: A Case Study with High Educational Teachers.Abdelbaset Almasri - 2017 - International Journal of Hybrid Information Technology 10 (12):1-12.
    Educational Data Mining (EDM) is a new paradigm aiming to mine and extract knowledge necessary to optimize the effectiveness of teaching process. With normal educational system work it’s often unlikely to accomplish fine system optimizing due to large amount of data being collected and tangled throughout the system. EDM resolves this problem by its capability to mine and explore these raw data and as a consequence of extracting knowledge. This paper describes several experiments on real educational data wherein the effectiveness (...)
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  36. Philosophical Signposts for Artificial Moral Agent Frameworks.Robert James M. Boyles - 2017 - Suri 6 (2):92–109.
    This article focuses on a particular issue under machine ethics—that is, the nature of Artificial Moral Agents. Machine ethics is a branch of artificial intelligence that looks into the moral status of artificial agents. Artificial moral agents, on the other hand, are artificial autonomous agents that possess moral value, as well as certain rights and responsibilities. This paper demonstrates that attempts to fully develop a theory that could possibly account for the nature of Artificial Moral Agents may consider certain philosophical (...)
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  37. Integrating Computer Vision Algorithms and Ontologies for Spectator Crowd Behavior Analysis.Davide Conigliaro, Celine Hudelot, Roberta Ferrario & Daniele Porello - 2017 - In Vittorio Murino, Marco Cristani, Shishir Shah & Silvio Savarese (eds.), Group and Crowd Behavior for Computer Vision, 1st Edition. pp. 297-319.
    In this paper, building on these previous works, we propose to go deeper into the understanding of crowd behavior by proposing an approach which integrates ontologi- cal models of crowd behavior and dedicated computer vision algorithms, with the aim of recognizing some targeted complex events happening in the playground from the observation of the spectator crowd behavior. In order to do that, we first propose an ontology encoding available knowledge on spectator crowd behavior, built as a spe- cialization of the (...)
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  38. ADO-Tutor: Intelligent Tutoring System for Leaning ADO.NET.Ibrahim A. El Haddad & Samy S. Abu Naser - 2017 - EUROPEAN ACADEMIC RESEARCH 4 (10).
    This paper describes an Intelligent Tutoring System for helping users with ADO.NET called ADO-Tutor. The Intelligent Tutoring System was designed and developed using (ITSB) authoring tool for building intelligent educational systems. The user learns through the intelligent tutoring system ADO.NET, the technology used by Microsoft.NET to connect to databases. The material includes lessons, examples, and questions. Through the feedback provided by the intelligent tutoring system, the user's understanding of the material is assessed, and accordingly can be guided to different difficulty (...)
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  39. Філософські Проблеми Ідеї Свідомої Машини.Konstantin Rayhert - 2017 - Схід 6 (152):104-107.
    The study outlines the existing and potential philosophical issues of the idea of conscious machines originated from the development of artificial consciousness within the framework of contemporary research of artificial intelligence and cognitive robotics. The outline shows that the idea of conscious machines is concerned with two big philosophical issues. The first philosophical issue is a definition of consciousness, taking into account the selection of a set of objects that can have consciousness, the typology of consciousness, the clarifying of the (...)
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  40. Artificial Intelligence In Software Engineering.Narendra Rao Tadapaneni - 2017 - Social Science Research Network 3.
    In the last few years, there has been a growing surge for the interest in the application of artificial intelligence in issues in Software Engineering (SE). Artificial Intelligence has become a much powerful and easy to use as they are increasingly deployed for different key components in the software system [1]. It enables the new functionalities and even allows much better adaptation to different user needs. This also creates additional issues for different software engineers and even exposes different firms to (...)
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  41. Non-Normal Modalities in Variants of Linear Logic.D. Porello & N. Troquard - 2015 - Journal of Applied Non-Classical Logics 25 (3):229-255.
    This article presents modal versions of resource-conscious logics. We concentrate on extensions of variants of linear logic with one minimal non-normal modality. In earlier work, where we investigated agency in multi-agent systems, we have shown that the results scale up to logics with multiple non-minimal modalities. Here, we start with the language of propositional intuitionistic linear logic without the additive disjunction, to which we add a modality. We provide an interpretation of this language on a class of Kripke resource models (...)
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  42. An Ontological Architecture for Orbital Debris Data.Robert J. Rovetto - 2015 - Earth Science Informatics 9 (1):67-82.
    The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris and broader SSA domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to (I) represent general orbital debris and SSA domain (...)
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  43. Causality and the Ontology of Disease.Robert J. Rovetto & Riichiro Mizoguchi - 2015 - Applied ontology 10 (2):79-105.
    The goal of this paper is two-fold: first, to emphasize causality in disease ontology and knowledge representation, presenting a general and cursory discussion of causality and causal chains; and second, to clarify and develop the River Flow Model of Diseases (RFM). The RFM is an ontological account of disease, representing the causal structure of pathology. It applies general knowledge of causality using the concept of causal chains. The river analogy of disease is explained, formal descriptions are offered, and the RFM (...)
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  44. Introduction: Formal Approaches to Multi-Agent Systems: Special Issue of Best Papers of FAMAS 2007.B. Dunin-Keplicz & R. Verbrugge - 2013 - Logic Journal of the IGPL 21 (3):309-310.
    Over the last decade, multi-agent systems have come to form one of the key tech- nologies for software development. The Formal Approaches to Multi-Agent Systems (FAMAS) workshop series brings together researchers from the fields of logic, theoreti- cal computer science and multi-agent systems in order to discuss formal techniques for specifying and verifying multi-agent systems. FAMAS addresses the issues of logics for multi-agent systems, formal methods for verification, for example model check- ing, and formal approaches to cooperation, multi-agent planning, communication, (...)
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  45. The Quest for Artificial Intelligence: A History of Ideas and Achievements. [REVIEW]Nils Nilsson - 2011 - Isis 102:588-589.
  46. SYSTEM UNDERSTANDING OF TRUTH AND PROBLEM OF ARTIFICIAL INTELLIGENCE.Artyom Ukhov - 2010 - RUDN Journal of Philosophy 2:93-96.
    The purpose of the article is to research the unseparable connection between objective aspects of cognition linked with metodology and logic and subjective ones which are covered to the subject’s mind and world outlook. According to psychology such a connection directly influences on understanding of truth and can be considered in the problem of artificial intelligence.
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  47. Hierarchical Differential Evolution for Parameter Estimation in Chemical Kinetics.Yuan Shi & Xing Zhong - 2008 - In Tu-Bao Ho & Zhi-Hua Zhou (eds.), Pricai 2008: Trends in Artificial Intelligence. Springer. pp. 870--879.
  48. Ambient Intelligence and Problems with Inferring Desires From Behaviour.Johnny Harz Soraker & Philip Brey - 2007 - International Review of Information Ethics 8:7-12.
    In this paper the authors argue that many of the ethical problems raised by Ambient Intelligence stems from presupposing a behaviourist conception of the relation between human desires and behaviour. Insofar as Ambient Intelligence systems take overt, natural behaviour as input, they are likely to suffer from many of the same problems that have fuelled the widespread criticism of behaviourist explanations of human behaviour. If these limitations of the technology are not sufficiently recognized, the technology is likely to be insufficiently (...)
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  49. Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983–1993. [REVIEW]Chris Gray - 2006 - Isis 97:188-189.
  50. Symbols Are Not Uniquely Human.Sidarta Ribeiro, Angelo Loula, Ivan Araújo, Ricardo Gudwin & Joao Queiroz - 2006 - Biosystems 90 (1):263-272.
    Modern semiotics is a branch of logics that formally defines symbol-based communication. In recent years, the semiotic classification of signs has been invoked to support the notion that symbols are uniquely human. Here we show that alarm-calls such as those used by African vervet monkeys (Cercopithecus aethiops), logically satisfy the semiotic definition of symbol. We also show that the acquisition of vocal symbols in vervet monkeys can be successfully simulated by a computer program based on minimal semiotic and neurobiological constraints. (...)
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